The present invention relates to a surface-roughness measuring apparatus, and more particularly to an improvement of a low-pass filter for extracting waviness-profile curve components from an detected profile curve.
A surface-roughness measuring apparatus is utilized for evaluating surface process accuracy of various machined workpieces. A stylus-type surface-roughness measuring apparatus includes a pickup comprising a stylus for tracing surface of an object to be measured and a detector for converting vibration detected by the stylus into an electric signal and amplifying the converted signal. At an output stage of the pickup provided are: an analog filter for filtering the signal from the pickup; an A/D converter for converting the filtered signal into digital data; and a data processing unit for processing the converted digital data.
An electric signal waveform detected by the pickup is referred to as an original profile curve. This original profile curve includes a waviness profile curve composed of low frequency components and a roughness curve composed of high frequency components. The roughness curve corresponds to small irregularity components constituting the surface roughness. A low-pass filter is used to obtain the waviness profile curve from the original unfiltered profile curve and a high-pass filter is used to obtain the roughness curve from the unfiltered profile curve. The roughness curve can also be obtained by subtracting the output of the low-pass filter (the waviness profile curve) from the original signal (unfiltered profile curve). The above described analog filter is used to perform the above-described filtering process. Similar filtering process can also be performed in a digital manner by the data processing unit without using the analog filter.
As described above, the roughness curve is obtained from the unfiltered profile curve by cutting the waviness profile curve components having wavelengths longer than a predetermined wavelength. The predetermined wavelength is called a cutoff value. Characteristic of low-pass filter for obtaining the waviness profile curve used for the surface roughness measuring has both domestic and international standards. These standards specify that the error between the frequency characteristic of the low-pass filter and the frequency characteristic of Gaussian filter be within a predetermined range. The Gaussian filter is a filter in which both an inpulse response of filter (a window function) and frequency characteristic exhibit the Gaussian function (a normal distribution function).
It has been known that an analog filter constituted by infinitely cascade-connected CR filters each having identical time-constant has a filter characteristic infinitely approximated to the ideal Gaussian filter.
In recent years, a digital filtering process is becoming popular in which the filtering process is performed by computer software in place of the analog filter. For example, German Patent No. 3,002,185 discloses a method for approximately realizing the Gaussian filter by cascade-connecting two finite inpulse response filters (FIR filters) each having a triangle window or a secondary infinite inpulse response filter (IIR filter).
However, the method of using ordinary IIR filters as the secondary filters has a large error. The use of the FIR filters permits the error to be reduced, but requires huge arithmetic operations, resulting in extremely increased operation time.